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Bibliographic Details
Main Authors:	Huang, Xingyue, Orth, Miguel Romero, Barceló, Pablo, Bronstein, Michael M., Ceylan, İsmail İlkan
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence
Online Access:	https://arxiv.org/abs/2402.04062
Tags:	Add Tag No Tags, Be the first to tag this record!

How Expressive are Knowledge Graph Foundation Models?
by: Huang, Xingyue, et al.
Published: (2025)

Cooperative Graph Neural Networks
by: Finkelshtein, Ben, et al.
Published: (2023)

One Model, Any Conjunctive Query: Graph Neural Networks for Answering Queries over Incomplete Knowledge Graphs
by: Olejniczak, Krzysztof, et al.
Published: (2024)

Fisher Flow Matching for Generative Modeling over Discrete Data
by: Davis, Oscar, et al.
Published: (2024)

Bringing Graphs to the Table: Zero-shot Node Classification via Tabular Foundation Models
by: Hayler, Adrian, et al.
Published: (2025)

What are the Right Symmetries for Formal Theorem Proving?
by: Olejniczak, Krzysztof, et al.
Published: (2026)

Explaining k-Nearest Neighbors: Abductive and Counterfactual Explanations
by: Barceló, Pablo, et al.
Published: (2025)

RelAgent: LLM Agents as Data Scientists for Relational Learning
by: Huang, Xingyue, et al.
Published: (2026)

Homomorphism Counts for Graph Neural Networks: All About That Basis
by: Jin, Emily, et al.
Published: (2024)

Flock: A Knowledge Graph Foundation Model via Learning on Random Walks
by: Kim, Jinwoo, et al.
Published: (2025)

Learning on Large Graphs using Intersecting Communities
by: Finkelshtein, Ben, et al.
Published: (2024)

Equivariance Everywhere All At Once: A Recipe for Graph Foundation Models
by: Finkelshtein, Ben, et al.
Published: (2025)

Future Directions in the Theory of Graph Machine Learning
by: Morris, Christopher, et al.
Published: (2024)

Homomorphism Counts as Structural Encodings for Graph Learning
by: Bao, Linus, et al.
Published: (2024)

MacroGuide: Topological Guidance for Macrocycle Generation
by: Maksymiuk, Alicja, et al.
Published: (2026)

A Neuro-Symbolic Framework for Answering Graph Pattern Queries in Knowledge Graphs
by: Cucumides, Tamara, et al.
Published: (2023)

Inductive Link Prediction on N-ary Relational Facts via Semantic Hypergraph Reasoning
by: Yin, Gongzhu, et al.
Published: (2025)

Self-Exploring Language Models for Explainable Link Forecasting on Temporal Graphs via Reinforcement Learning
by: Ding, Zifeng, et al.
Published: (2025)

Ehrenfeucht-Haussler Rank and Chain of Thought
by: Barceló, Pablo, et al.
Published: (2025)

Hyperbolic Hypergraph Neural Networks for Multi-Relational Knowledge Hypergraph Representation
by: Li, Mengfan, et al.
Published: (2024)

Zero-One Laws of Graph Neural Networks
by: Adam-Day, Sam, et al.
Published: (2023)

Curly Flow Matching for Learning Non-gradient Field Dynamics
by: Petrović, Katarina, et al.
Published: (2025)

Effective Sample Size and Generalization Bounds for Temporal Networks
by: Gahtan, Barak, et al.
Published: (2025)

Almost Surely Asymptotically Constant Graph Neural Networks
by: Adam-Day, Sam, et al.
Published: (2024)

Mathematical Foundations of Geometric Deep Learning
by: Borde, Haitz Sáez de Ocáriz, et al.
Published: (2025)

Over-squashing in Spatiotemporal Graph Neural Networks
by: Marisca, Ivan, et al.
Published: (2025)

gLSTM: Mitigating Over-Squashing by Increasing Storage Capacity
by: Blayney, Hugh, et al.
Published: (2025)

Dynamic Hypergraph-Enhanced Prediction of Sequential Medical Visits
by: Yang, Wangying, et al.
Published: (2024)

Self-Explaining Hypergraph Neural Networks for Diagnosis Prediction
by: Yu, Leisheng, et al.
Published: (2025)

MaGNet: A Mamba Dual-Hypergraph Network for Stock Prediction via Temporal-Causal and Global Relational Learning
by: Tan, Peilin, et al.
Published: (2025)

Supercharging Graph Transformers with Advective Diffusion
by: Wu, Qitian, et al.
Published: (2023)

LLMs can hide text in other text of the same length
by: Norelli, Antonio, et al.
Published: (2025)

Categorical Flow Maps
by: Roos, Daan, et al.
Published: (2026)

Multi-Relational Graph Neural Network for Out-of-Domain Link Prediction
by: Sattar, Asma, et al.
Published: (2024)

A Mechanistic Analysis of Looped Reasoning Language Models
by: Blayney, Hugh, et al.
Published: (2026)

Message Passing on the Edge: Towards Scalable and Expressive GNNs
by: Barceló, Pablo, et al.
Published: (2025)

Relational Learning in Pre-Trained Models: A Theory from Hypergraph Recovery Perspective
by: Chen, Yang, et al.
Published: (2024)

Predicting Time Series of Networked Dynamical Systems without Knowing Topology
by: Ding, Yanna, et al.
Published: (2024)

On Measuring Long-Range Interactions in Graph Neural Networks
by: Bamberger, Jacob, et al.
Published: (2025)

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// Anecdotal testing Today and Yesterday seems to indicate destroy() // is called by the garbage collector and everything is good. // Something to keep in mind though. return 0; } /** * Write function that is called when session data is to be saved. * * @param string $sessId The current session ID * @param string $data The session data to write * * @return bool */ public function write($sessId, $data): bool { if ($this->writesDisabled) { return true; } return $this->saveSession($sessId, $data); } /** * A function that is called internally when session data is to be saved. * * @param string $sessId The current session ID * @param string $data The session data to write * * @return bool */ abstract protected function saveSession($sessId, $data): bool; }

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